A new method for image segmentation

On the basis of analyzing the blur images with noise, this paper presents a new segmentation method which is based on the morphology method, fuzzy K-means algorithm and some parts operator of the Canny algorithm. Because of the Canny's good performance on good detection, good localization and o...

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Bibliographic Details
Published in:2009 Asia-Pacific Conference on Computational Intelligence and Industrial Applications Vol. 2; pp. 123 - 125
Main Authors: Wang Guitang, Zhu Jianlin, Wei Qingchun, Xin Huasheng, Cao Peiliang
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2009
Subjects:
Algorithm design and analysis
Canny operator
Charge coupled devices
Charge-coupled image sensors
Clustering algorithms
edge detection
Fuzzy control
fuzzy K-means algorithm
Image analysis
Image edge detection
Image segmentation
mathematical morphology
Morphology
Noise figure
ISBN:1424446066, 9781424446063
Online Access:Get full text
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Summary:On the basis of analyzing the blur images with noise, this paper presents a new segmentation method which is based on the morphology method, fuzzy K-means algorithm and some parts operator of the Canny algorithm. Because of the Canny's good performance on good detection, good localization and only one response to a single edge, we introduce the course of Canny operator that calculating the value and direction of grads, non-maxima suppression to the grad value and lag threshold process into our post-treatment process. Through experiments, it is demonstrated that the image segmentation method in this paper is very effective.
ISBN:1424446066
9781424446063
DOI:10.1109/PACIIA.2009.5406610